progressive generative adversarial networks for medical image super resolution用于医学图像渐进生成对抗网络超级分辨率.pdf
文本预览下载声明
9
1
0
2
b
e
F
显示全部
文档详情
相似文档
-
multi-view aware attention networks for image super resolution图像超分辨率多视图意识到注意网络.pdf
MAANet:Multi-viewAwareAtentionNetworks
forImageSuper-Resolution
JingcaiGuoShihengMaSongGuo
PolytechnicUniversity
-
image super-resolution using very deep residual channel attention networks使用非常深残留通道注意网络图像超分辨率.pdf
ImageSuper-ResolutionUsingVeryDeep
ResidualChannelAttentionNetworks
YulunZhang1[0000−0002−2288−5079],KunpengLi1[0000−0001−5805−793X],Kai
Li1[0000−0002−9027−0914],LichenWang1[0000−0002−3741−9492],Bineng
Zhong1[0000−0003−3423−1539],andYunFu1,2[0000−0002−8588−5084]
1DepartmentofECE,NortheasternUniversi
-
learning deep convolutional network for image super-resolution学习深层卷积网络以进行超级分辨率.pdf
-
srfeatsingle image super resolution with feature图像超级分辨率具有特征歧视.pdf
SRFeat:SingleImageSuper-Resolution
withFeatureDiscrimination
1121
Seong-JinPark,HyeongseokSon,SunghyunCho,Ki-SangHong,
-
second-order attention network for single image super resolution单图超分辨率二阶注意网络.pdf
Second-orderAttentionNetworkforSingleImageSuper-Resolution
1,2,∗,‡3,∗11,23,4,§
TaoDai,JianruiCai,YongbingZhang,Shu-TaoXia,LeiZhang
1GraduateSchoolatShenzhen,TsinghuaUniversity,Shenzhen,
2PCLResearchCenterofNetworksandCommunications,PengChengLaboratory,Shenzhen,
3DepartmentofComputing,ThePolytechnicU
-
unsupervised sparse dirichlet-net for hyperspectral image resolution无监督稀疏用于高光谱图像超分辨率.pdf
UnsupervisedSparseDirichlet-NetforHyperspectralImageSuper-Resolution
112
YingQu*,HairongQi,ChimanKwan
1TheUniversity
-
face image super-resolution through locality induced support regression面部图像通过区域诱导支持回归进行超级分辨率.pdf
SignalProcessing103(2014)168–183
ContentslistsavailableatScienceDirect
SignalProcessing
-
super-resolution of images based local correlations基于局部相关图像超级分辨率.pdf
SUPER-RESOLUTIONOFIMAGESBASEDONLOCALCORRELATIONS
FrankM.CandociaJoseC.Principe
candocia@principe@
-
manifold regularized sparse support regression for single image super-resolution单图超分辨率歧管正则稀疏支持回归.pdf
MANIFOLDREGULARIZEDSPARSESUPPORTREGRESSIONFORSINGLE
IMAGESUPER-RESOLUTION
JunjunJiang,RuiminHu,ZhongyuanWang,ZhenHan,andShiDong
NationalEngineeringResearchCenterforMultimediaSoftware,SchoolofComputer,
WuhanUniversity,Wuhan,430072,China
Email:{jiangjunjun,hrm1964,wzy_hope,hanzhen,dongshi}
Yangetal.em
-
fast spatio-temporal residual network for video super resolution超分辨率快速时空残差网络.pdf
FastSpatio-TemporalResidualNetworkforSuper-Resolution
121132
ShengLi,FengxiangHe,BoD
-
recurrent back-projection network for video super resolution超分辨率反复反射网络.pdf
(a)Temporalconcatenation(b)Temporalaggregation(c)RNNs(d)OurRBPN
Figure1.ComparisonofDeepVSRs.(a)Inputframesareconcatenatedtopreservetemporalinformation[18,2,16,22].(b)Temporal
aggregationimproves(a)topr
-
基于生成对抗网络的医学图像超分辨率算法研究.pdf
基于生成对抗网络的医学图像超分辨率算法研究
摘要
医学图像是利用医学成像设备及技术，获得人体内部器官或组织的形态结构、病
理状态而得到的图像，其中磁共振成像凭借其安全、快速、准确的优点，在临床医学
上应用广泛。然而，由于高质量的磁共振成像通常伴随着长时间的扫描采集和昂贵的
成本，所以现存的磁共振图像通常分辨率较低，可能会造成诊断上的障碍和辅助诊断
模型训练上的困难。所以研究一种有效的医学超分辨率算法，可以在不改动硬件设备
的前提下，将低分辨率图像重建为纹理细节更加清晰的高分辨率图像具有重要的现实
意义。本文以构造有效的下采样算法和提升超分辨率算法在真实低清医学图像上的超
分效果为目标，对基于生
-
31 semi-coupled dictionary learning with applications image super resolution and photo sketch synthesis31半耦合词典学习并应用于图像超分辨率照片佐剂合成.pdf
Semi-CoupledDictionaryLearningwithApplicationstoImageSuper-Resolution
andPhoto-SketchSynthesis
ShenlongWangLeiZhangYanLiangQuanPan
NorthwesternPolytechnicalUniversity,TheHongKongPolytechnicUniversity
shenlong.wang@,cslzhang@.hk,liangyan@,quanpan@
Abstractderstandhowthehumanvisualsystemperceivesthedi
-
unsupervised and unregistered hyperspectral image-resolution with mutual dirichlet net无监督注册高光谱图像超分辨率与互助网络.pdf
1
UnsupervisedandUnregisteredHyperspectral
ImageSuper-ResolutionwithMutualDirichlet-Net
-
guided super-resolution as learned pixel to transformation指导超级分辨率学习像素到转换.pdf
GuidedSuper-ResolutionasaLearnedPixel-to-Pixel
Transformation
1111